Antiretroviral Drug Transporters and Metabolic Enzymes in Circulating Monocytes and Monocyte-Derived Macrophages of ART-Treated People Living With HIV and HIV-Uninfected Individuals
Bibliographic record
Abstract
ABSTRACT: Membrane-associated drug transport proteins and drug metabolic enzymes could regulate intracellular antiretroviral (ARV) drug concentrations in HIV-1 target cells such as myeloid cells. We investigated the expression of these transporters and enzymes in monocyte subsets and monocyte-derived macrophages (MDMs) isolated from peripheral blood mononuclear cells (PBMCs) of HIV-uninfected individuals (HIV-negative) and people living with HIV receiving viral suppressive antiretroviral therapy (ART; HIV+ART) and examined plasma and intracellular ARV concentrations. Monocytes were isolated from PBMCs of 12 HIV-negative and 12 HIV+ART donors and differentiated into MDMs. The mRNA and protein expression of drug transporters and metabolic enzymes were analyzed by quantitative real-time polymerase chain reaction and flow cytometry, respectively. ARV drug concentrations were quantified in plasma, PBMCs, monocytes, and MDMs by LC-MS/MS. The mRNA expression of relevant ARV transporters or metabolic enzymes, ABCB1/P-gp, ABCG2/BCRP, ABCC1/MRP1, ABCC4/MRP4, SLC22A1/OCT1, SLC29A2/ENT2, CYP2B6, CYP2D6, and UGT1A1, was demonstrated in monocytes and MDMs of 2 to 4 HIV-negative donors. P-gp, BCRP, and MRP1 proteins were differentially expressed in classical, intermediate, and nonclassical monocytes and MDMs of both HIV+ART and HIV-negative donors. Intracellular concentrations of ARVs known to be substrates of these transporters and metabolic enzymes were detected in monocytes of HIV+ART donors but were undetectable in MDMs. In this study, we demonstrated the expression of drug transporters and metabolic enzymes in monocytes and MDMs of HIV-negative and HIV+ART individuals, which could potentially limit intracellular concentrations of ARVs and contribute to residual HIV replication. Further work is needed to assess the role of these transporters in the penetration of ARVs in tissue macrophages.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".